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Mr. Serhan Cevik and John Ricco

estimations, we treat the dependent variable, real GDP per capita and consumer price inflation as endogenous and the terrorism indicator and other control variables as exogenous. In military spending estimations, we treat the dependent variable, real GDP per capita and trade openness as endogenous and the terrorism indicator and other control variables as exogenous. To avoid a proliferation of instruments, we collapse the instrument set as suggested by Roodman (2009) . We validate the system GMM identification assumptions by applying a second-order serial correlation test

Mr. Serhan Cevik and Mr. Manuk Ghazanchyan
While the world’s attention is on dealing with the COVID-19 pandemic, climate change remains a greater existential threat to vulnerable countries that are highly dependent on a weather-sensitive sector like tourism. Using a novel multidimensional index, this study investigates the long-term impact of climate change vulnerability on international tourism in a panel of 15 Caribbean countries over the period 1995–2017. Empirical results show that climate vulnerability already has a statistically and economically significant negative effect on international tourism revenues across the region. As extreme weather events are becoming more frequent and severe over time, our findings indicate that the Caribbean countries need to pursue comprehensive adaptation policies to reduce vulnerabilities to climate change.
Mr. Serhan Cevik and Mr. Manuk Ghazanchyan

potentially leads to over-fitting. Also, the use of a large set of instruments weakens the Hansen J-test of over-identifying restrictions, making it difficult to detect over-identification problems over loss of information. Accordingly, estimating such models requires a subtle balance between maximizing the information obtained from the panel data , and safeguarding against over-identification. We follow Roodman (2009) to address this issue. We also corroborate the system GMM identification assumptions by performing a second-order serial correlation test for the

Mr. Serhan Cevik and Tianle Zhu
Monetary independence is at the core of the macroeconomic policy trilemma stating that an independent monetary policy, a fixed exchange rate and free movement of capital cannot exist at the same time. This study examines the relationship between monetary autonomy and inflation dynamics in a panel of Caribbean countries over the period 1980–2017. The empirical results show that monetary independence is a significant factor in determining inflation, even after controlling for macroeconomic developments. In other words, greater monetary policy independence, measured as a country’s ability to conduct its own monetary policy for domestic purposes independent of external monetary influences, leads to lower consumer price inflation. This relationship—robust to alternative specifications and estimation methodologies—has clear policy implications, especially for countries that maintain pegged exchange rates relative to the U.S. dollar with a critical bearing on monetary autonomy.
Mr. Serhan Cevik and João Tovar Jalles
Climate change is already a systemic risk to the global economy. While there is a large body of literature documenting potential economic consequences, there is scarce research on the link between climate change and sovereign risk. This paper therefore investigates the impact of climate change vulnerability and resilience on sovereign bond yields and spreads in 98 advanced and developing countries over the period 1995–2017. We find that the vulnerability and resilience to climate change have a significant impact on the cost government borrowing, after controlling for conventional determinants of sovereign risk. That is, countries that are more resilient to climate change have lower bond yields and spreads relative to countries with greater vulnerability to risks associated with climate change. Furthermore, partitioning the sample into country groups reveals that the magnitude and statistical significance of these effects are much greater in developing countries with weaker capacity to adapt to and mitigate the consequences of climate change.
Mr. Serhan Cevik and João Tovar Jalles

hardest when it is most needed. Conversely, however, restricting the instrument set too much results in a loss of information that leads to imprecisely estimated coefficients. Estimation of such models therefore involves a delicate balance between maximizing the information extracted from the data on the one hand, and guarding against over-identification on the other. To this end, we follow the strategy suggested by Roodman (2009) to deal with the problem of weak and excessively numerous instruments. We also validate the system GMM identification assumptions by applying

Mr. Serhan Cevik and Vibha Nanda

validate the system GMM identification assumptions by applying a second-order serial correlation test for the residuals and the Hansen J -test for overidentifying restrictions. In all the regressions, the p values of the Arellano-Bond (AR) autocorrelation test and the Hansen J -test results confirm the absence of second-order serial correlation in the error term of the first-difference equation and the validity of internal instruments. The empirical results, presented in Table 2 , show a consistent picture across different model specifications and estimation

Mr. Serhan Cevik and Tianle Zhu

guarding against over-identification on the other. To this end, we follow the strategy suggested by Roodman (2009) to deal with the problem of weak and excessively numerous instruments. We also validate the system GMM identification assumptions by applying a second-order serial correlation test for the residuals and the Hansen J -test for the overidentifying restrictions. The values reported for AR(1) and AR(2) in Table 1 for baseline results and Appendix Table 3 for robustness checks are the p -values for first- and second-order autocorrelated disturbances in